CN116879920B - Dyke quality detection method and system based on laser point cloud technology - Google Patents
Dyke quality detection method and system based on laser point cloud technology Download PDFInfo
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- G—PHYSICS
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
- G01S17/89—Lidar systems specially adapted for specific applications for mapping or imaging
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Abstract
The disclosure provides a dam quality detection method and system based on a laser point cloud technology, and relates to the technical field of quality detection, wherein the method comprises the following steps: data acquisition is carried out on the target dykes and dams based on binocular cameras, and a target space three-dimensional coordinate system is constructed; scanning the target dykes and dams by a laser point cloud technology to obtain N scanning points of the target dykes and dams distributed in a target space three-dimensional coordinate system; connecting in a target space three-dimensional coordinate system, and determining target dam three-dimensional structure information; performing information matching on the target dam three-dimensional structure information and a dam structure information base to obtain dam structure matching data; performing coverage traversal on the dam structure matching data to obtain coverage traversal data; stability detection is carried out on the structure of the target dykes and dams according to the coverage traversal data, quality detection results of the target dykes and dams are obtained according to the detection results, and the detection environment influence can be reduced through the method and the device, and the effects of improving detection precision and detection efficiency are achieved.
Description
Technical Field
The disclosure relates to the technical field of quality detection, in particular to a dam quality detection method and system based on a laser point cloud technology.
Background
The river systems in China are numerous, and the coastline is long. Embankment facilities of tens of thousands of kilometers are built on river sides and seasides to protect life safety of residents along the river and coastal areas and ensure economic development. In recent years, economic losses caused by storm dikes are larger and larger, and safety inspection requirements of each party on the flood dikes and the sea dikes are also stricter. At present, most of the monitoring methods of the dikes in China are combined with manual observation and manual inspection so as to ensure the safety of the dikes. However, the manual observation and the manual inspection are affected by the dam area environment, weather and light, and the phenomena of low observation precision, high labor intensity and large influence by the environment exist, especially in the flood season or typhoon multiple-occurrence period. The manual observation mode cannot meet the requirements of dam safety detection, and seriously affects the safety management level, so that a method for detecting the dam is needed.
In summary, in the prior art, because the manual detection is greatly affected by the environment, the detection precision is low and the detection efficiency is low.
Disclosure of Invention
The disclosure provides a dam quality detection method and system based on a laser point cloud technology, which are used for solving the technical problems of low detection precision and low detection efficiency caused by large influence of manual detection on environment in the prior art.
According to a first aspect of the present disclosure, there is provided a dyke quality detection method based on a laser point cloud technology, including: based on the binocular camera, data acquisition is carried out on the target dykes and dams, and a target space three-dimensional coordinate system is constructed; scanning the target dykes and dams through a laser point cloud technology to obtain N scanning points of the target dykes and dams distributed in the target space three-dimensional coordinate system, wherein N is a positive integer greater than 3; connecting the N scanning points in the target space three-dimensional coordinate system to determine the three-dimensional structure information of the target dam; performing information matching on the target dam three-dimensional structure information and a dam structure information base to obtain dam structure matching data; performing coverage traversal on the dam structure matching data to obtain coverage traversal data, wherein the coverage traversal data comprises traversal abnormal combination data; and detecting the stability of the structure of the target dykes and dams according to the coverage traversal data, and acquiring the quality detection result of the target dykes and dams according to the detection result.
According to a second aspect of the present disclosure, there is provided a dyke quality detection system based on a laser point cloud technology, comprising: the target space three-dimensional coordinate system construction module is used for carrying out data acquisition on the target dykes and dams based on the binocular cameras and constructing a target space three-dimensional coordinate system; the scanning point position obtaining module is used for scanning the target dykes and dams through a laser point cloud technology to obtain N scanning point positions of the target dykes and dams distributed in the target space three-dimensional coordinate system, wherein N is a positive integer greater than 3; the target dam three-dimensional structure information acquisition module is used for connecting the N scanning points in the target space three-dimensional coordinate system and determining target dam three-dimensional structure information; the dam structure matching data acquisition module is used for carrying out information matching on the target dam three-dimensional structure information and a dam structure information base to acquire dam structure matching data; the coverage traversal data acquisition module is used for carrying out coverage traversal on the dam structure matching data to acquire coverage traversal data, wherein the coverage traversal data comprises traversal abnormal combination data; the quality detection result obtaining module is used for detecting the stability of the structure of the target dykes and dams according to the coverage traversal data and obtaining the quality detection result of the target dykes and dams according to the detection result.
One or more technical solutions provided in the present application have at least the following technical effects or advantages: according to the method, the target dam is subjected to data acquisition based on the binocular camera, and a target space three-dimensional coordinate system is constructed; scanning the target dykes and dams through a laser point cloud technology to obtain N scanning points of the target dykes and dams distributed in the target space three-dimensional coordinate system, wherein N is a positive integer greater than 3; connecting the N scanning points in the target space three-dimensional coordinate system to determine the three-dimensional structure information of the target dam; performing information matching on the target dam three-dimensional structure information and a dam structure information base to obtain dam structure matching data; performing coverage traversal on the dam structure matching data to obtain coverage traversal data, wherein the coverage traversal data comprises traversal abnormal combination data; and carrying out stability detection on the structure of the target dykes and dams according to the coverage traversal data, and obtaining the quality detection result of the target dykes and dams according to the detection result, so that the influence of detection environment can be reduced, and the technical effects of improving the detection precision and the detection efficiency are realized.
It should be understood that the description of this section is not intended to identify key or critical features of the embodiments of the disclosure, nor is it intended to be used to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following specification.
Drawings
For a clearer description of the present disclosure or of the prior art, the drawings used in the description of the embodiments or of the prior art will be briefly described, it being obvious that the drawings in the description below are only exemplary and that other drawings may be obtained, without inventive effort, by a person skilled in the art, from the provided drawings.
Fig. 1 is a schematic flow chart of a dam quality detection method based on a laser point cloud technology according to an embodiment of the disclosure;
fig. 2 is a schematic flow chart of constructing a three-dimensional coordinate system of a target space in a dam quality detection method based on a laser point cloud technology according to an embodiment of the disclosure;
fig. 3 is a schematic flow chart of acquiring N scanning points of the target dam distributed in a target space three-dimensional coordinate system in a dam quality detection method based on a laser point cloud technology according to an embodiment of the disclosure;
fig. 4 is a schematic flow chart of determining three-dimensional structure information of a target dam in a dam quality detection method based on a laser point cloud technology according to an embodiment of the disclosure;
fig. 5 is a schematic structural diagram of a dam quality detection system based on a laser point cloud technology according to an embodiment of the present disclosure.
Reference numerals illustrate: the system comprises a target space three-dimensional coordinate system construction module 11, a scanning point position obtaining module 12, a target dam three-dimensional structure information obtaining module 13, a dam structure matching data obtaining module 14, a coverage traversal data obtaining module 15 and a quality detection result obtaining module 16.
Detailed Description
Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and should be considered as merely exemplary. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
In order to solve the technical problems of low detection precision and low detection efficiency caused by large influence of manual detection on environment in the prior art, the inventor of the present disclosure obtains a dyke quality detection method and system based on a laser point cloud technology through creative labor:
example 1
Fig. 1 is a block quality detection method based on a laser point cloud technology according to an embodiment of the present application, where the method includes:
step S100: based on the binocular camera, data acquisition is carried out on the target dykes and dams, and a target space three-dimensional coordinate system is constructed;
specifically, a binocular camera is a device that acquires the depth or distance of a target object by capturing two target objects. Further, data acquisition is carried out on the target dykes and dams based on the binocular cameras. Wherein the target dike is a dike to be subjected to quality detection. Further, the internal parameters of the single camera are calibrated, and parameters such as the focal length, the optical center, the distortion coefficient and the like of each camera are obtained. And calibrating the external parameters of the binocular cameras to obtain the rotation and translation relation of the camera coordinate system between the binocular cameras, and generating a calibration result of the cameras. And correcting the original images of the target dykes acquired by the two cameras according to the calibration results of the cameras, wherein the corrected target dykes are positioned on the same plane and are parallel to each other, namely, the corrected target dykes are collinear among each row of pixels of the target dykes, so that a three-dimensional correction result is obtained. And according to the image subjected to the stereo correction, matching pixel points, wherein the successfully matched points represent different positions of a certain point in the real world in the two target dyke images, and a stereo matching result is obtained. And obtaining a parallax image according to the stereo matching result, and calculating the depth corresponding to each pixel through the parallax image, so as to obtain a target dyke depth image, namely the distance between each point of the target dykes and the camera.
Further, one point of the target dam is randomly extracted as an origin. And obtaining the distance between the origin of the target dyke and the binocular camera according to the depth map of the target dyke. And acquiring the height, the length and the width of the target dam through big data. Further, according to the origin of the target dykes and dams, coordinate axes are constructed through the height, the length and the width of the target dykes and dams, and a target space three-dimensional coordinate system of the target dykes and dams is obtained, so that the effect of obtaining the target dykes and dams structure is achieved.
Step S200: scanning the target dykes and dams through a laser point cloud technology to obtain N scanning points of the target dykes and dams distributed in the target space three-dimensional coordinate system, wherein N is a positive integer greater than 3;
specifically, the laser point cloud technology of the laser point cloud device is used for carrying out surface scanning on the target dykes and obtaining laser beams reflected by a plurality of target dykes. And extracting the laser beams reflected by the target dykes and dams, and converting the laser beams into three-dimensional coordinate points in a three-dimensional coordinate system of the target space, so that N scanning points of the target dykes and dams are obtained. The N scanning points at least comprise a height scanning point position, a length scanning point position and a width scanning point position of the target dykes, so that N is a positive integer larger than 3, and the function of acquiring the scanning structure of the target dykes is realized.
Step S300: connecting the N scanning points in the target space three-dimensional coordinate system to determine the three-dimensional structure information of the target dam;
specifically, coordinate information of N scan sites is acquired. And connecting the N scanning points in a target space three-dimensional coordinate system in a pairwise manner to obtain a plurality of connecting lines. And calculating the lengths of the connecting lines according to the coordinate information of the N scanning sites. According to the coordinate information of the N scanning sites and the lengths of the connecting lines, three-dimensional data information of the target dykes and dams in a target space three-dimensional coordinate system is obtained, and further three-dimensional structure information of the target dykes and dams is determined, so that the effect of obtaining the three-dimensional structure of the target dykes and dams is achieved.
Step S400: performing information matching on the target dam three-dimensional structure information and a dam structure information base to obtain dam structure matching data;
specifically, a bank structure information base is acquired through big data. The dyke structure information base comprises decomposition structure information of preset dyke structure information. Further, the three-dimensional structure information of the target dykes is decomposed, and decomposition structure information of a plurality of target dykes is obtained. Further, the decomposition structure information of the plurality of target dykes and the decomposition structure information of the preset dykes and dams in the dykes structure information base are sequentially compared, and a plurality of decomposition structure information matching degrees are obtained. Further, the matching degree of a plurality of decomposition structure information is combined, dam structure matching data are obtained, and the function of obtaining abnormal matching results is achieved.
Step S500: performing coverage traversal on the dam structure matching data to obtain coverage traversal data, wherein the coverage traversal data comprises traversal abnormal combination data;
specifically, preset dike combination data is acquired based on the big data. Further, covering traversal is sequentially conducted on the dam structure matching data, the dam structure matching data are matched with preset dam combination data, a plurality of matching results are generated, and covering traversal data are obtained. Further, dyke structure data in the unmatched result is extracted as traversal abnormal combination data. The extraction traversal abnormal combination data is added to the coverage traversal data, so that the function of detecting abnormal structures or quality is realized.
Step S600: and detecting the stability of the structure of the target dykes and dams according to the coverage traversal data, and acquiring the quality detection result of the target dykes and dams according to the detection result.
Specifically, according to the unmatched results in the coverage traversal data, stability of the dam combination data in the unmatched results is detected, and a stability detection result is obtained. And extracting dam combination data with stronger stability from the stability detection result, and carrying out quality better identification. Further, a plurality of quality identifiers are combined to obtain a quality detection result of the target dam, and the effect of improving the detection precision is achieved.
The detection environment influence can be reduced through the embodiment, and the effects of improving the detection precision and the detection efficiency are achieved.
As shown in fig. 2, step S100 in the method provided in the embodiment of the present application includes:
s110: determining a target original site through the binocular camera;
s120: constructing a first coordinate axis through the height of the target dykes based on the target original sites;
s130: constructing a second coordinate axis through the length of the target dykes based on the target original sites;
s140: constructing a third coordinate axis through the width of the target dykes based on the target original sites;
s150: and constructing a target space three-dimensional coordinate system of the target dam based on the first coordinate axis, the second coordinate axis and the third coordinate axis respectively.
Specifically, shooting the target dykes and dams through the binocular cameras, and obtaining a depth map of the target dykes and dams. Wherein, randomly extracting a point of the target dykes and determining the target original site serving as the target dykes. And extracting a target original site of the target dyke, and obtaining the distance between the target original site and the binocular camera.
Further, based on the big data, searching is performed by taking the height of the target dike as an index condition, and the height of the target dike is obtained. And constructing a first coordinate axis according to the target original site of the target dam by the height of the target dam, and obtaining the height coordinate of the target dam. Further, based on the big data, searching is performed by taking the target dykes and dams length as an index condition, and the length of the target dykes and dams is obtained. And constructing a second coordinate axis according to the target original site of the target dam by the length of the target dam, and obtaining the length coordinate of the target dam. Further, based on the big data, searching is performed by taking the width of the target dykes as an index condition, and the width of the target dykes is obtained. And constructing a third coordinate axis through the width of the target dam according to the target original site of the target dam, and obtaining the width coordinate of the target dam.
Further, the first coordinate axis, the second coordinate axis and the third coordinate axis are respectively extracted, and a target space three-dimensional coordinate system of the target dam is constructed.
The method comprises the steps of constructing a target space coordinate system of the target dykes and dams, and helping to acquire the structures of the target dykes and dams so as to detect the target dykes and dams.
As shown in fig. 3, step S200 in the method provided in the embodiment of the present application includes:
s210: the target dam is scanned point by point through a laser radar in the laser point cloud technology, and a plurality of scanning reflection points are determined, wherein each scanning reflection point in the plurality of scanning reflection points comprises a laser beam;
s220: the laser beams are arranged in the target space three-dimensional coordinate system in a same ratio mode, and three-dimensional coordinates of the scanning reflection points are obtained;
s230: the N scan points are determined based on the three-dimensional coordinates of the plurality of scan reflection points.
Specifically, the lidar device is a device for detecting an object having a low radio wave reflectivity or a distance and a positional relationship with surrounding obstacles by scanning with a lidar detector, is not affected by ambient light, and obtains high-precision, dense three-dimensional model data. In the present embodiment, a laser radar in a laser point cloud technology performs point-by-point scanning by emitting a laser beam to a target bank, and receives the laser beam to determine a plurality of scanning reflection points. Wherein each of the plurality of scanning reflection points comprises a laser beam.
Further, based on the plurality of laser beams, a plurality of relative positions of the plurality of scanning reflection points are acquired. And extracting the relative positions of the plurality of scanning reflection points, and configuring the relative positions in the target space three-dimensional coordinate system according to the same proportion of the relative positions to obtain the three-dimensional coordinates of the plurality of scanning reflection points. Further, three-dimensional coordinates of the plurality of scanning reflection points are extracted, and N scanning points are determined.
The method comprises the steps of acquiring N scanning points in a three-dimensional coordinate system of a target space, and facilitating the acquisition of structural data of a target dam so as to detect the target dam.
As shown in fig. 4, step S300 in the method provided in the embodiment of the present application includes:
s310: extracting a first scanning point position and a second scanning point position of the N scanning point positions, wherein the first scanning point position and the second scanning point position are two adjacent point positions;
s320: performing point location connection on the first scanning point location and the second scanning point location to obtain a plurality of connecting lines;
s330: establishing three-dimensional data of the target dike based on the plurality of connecting lines;
s340: and constructing the three-dimensional structure information of the target dam according to the three-dimensional data.
Specifically, based on N scan points, one scan point is randomly extracted as a first scan point. Extracting a plurality of adjacent points of the first scanning point, and randomly extracting one point of the plurality of adjacent points to serve as a second scanning point. Further, the first scanning point location and the second scanning point location are extracted. And performing point location connection on the first scanning point location and the second scanning point location to obtain a connecting line of the first scanning point location and the second scanning point location.
Further, based on the N scan points, another scan point is randomly extracted as the updated first scan point. Extracting a plurality of updating adjacent points for updating the first scanning point, and randomly extracting one point of the plurality of updating adjacent points to serve as an updating second scanning point. Extracting and updating the first scanning point position and updating the second scanning point position. And performing point location connection on the updated first scanning point location and the updated second scanning point location to obtain a connecting line of the updated first scanning point location and the updated second scanning point location.
Further, a first scanning point and a second scanning point in the N scanning points are sequentially connected, and a connecting line of the first scanning point and the second scanning point is obtained. And connecting all the N scanning points in pairs to obtain a plurality of connecting lines.
Further, according to the target space three-dimensional coordinate system, two scanning points of each connecting line in the plurality of connecting lines, namely a first scanning point and a second scanning point, are extracted, and coordinates of the two scanning points are obtained. And calculating and obtaining the length of the connecting line of the first scanning point and the second scanning point according to the coordinates of the two scanning points. Thereby obtaining the lengths of a plurality of connecting wires. Further, three-dimensional data of the target dike is established according to the lengths of the plurality of connecting lines. Further, according to the three-dimensional data of the target dykes and dams, constructing three-dimensional structure information in a target space three-dimensional coordinate system of the target dykes and dams.
The method comprises the steps of acquiring three-dimensional structure information of a target dam, and helping to acquire the three-dimensional structure data information of the target dam so as to detect the target dam.
Step S400 in the method provided in the embodiment of the present application includes:
s410: performing structural decomposition on dam structure information in big data to obtain preset dam body structure information, preset dam head structure information and preset dam root structure information;
s420: performing structural decomposition on the target dam three-dimensional structure information to obtain dam body structure information, dam head structure information and dam foundation structure information;
s430: sequentially comparing the preset dam body structure information, the preset dam head structure information, the preset dam root structure information with the dam body structure information, the dam head structure information and the dam root structure information to obtain a dam body structure information matching degree, a dam head structure information matching degree and a dam root structure information matching degree;
s440: and determining the dam structure matching data according to the dam body structure information matching degree, the dam head structure information matching degree and the dam root structure information matching degree.
Specifically, based on the big data, the dam structure is used as an index condition to search and acquire the dam structure information. The obtaining of the dam structure information may be common dam structure information. Further, structural decomposition is carried out on the dam structure information, and preset dam body structure information, preset dam head structure information and preset dam foundation structure information are obtained. Further, structural decomposition is carried out on the three-dimensional structural information of the target dam to obtain dam body structural information, dam head structural information and dam foundation structural information.
Further, the dam body structure information is compared with preset dam body structure information, and the matching degree of the dam body structure information is obtained. And comparing the dam head structure information with preset dam head structure information to obtain the matching degree of the dam head structure information. And comparing the dam foundation structure information with preset dam foundation structure information to obtain the matching degree of the dam foundation structure information. Further, dam structure matching data are integrated and determined according to the dam body structure information matching degree, the dam head structure information matching degree and the dam root structure information matching degree.
The method comprises the steps of obtaining dam structure matching data, and obtaining dam structure combination abnormality and incomplete abnormality data, so as to obtain a detection result.
Step S500 in the method provided in the embodiment of the present application includes:
s510: acquiring dyke-dam combination data based on a data terminal of the dyke-dam structure;
s520: correspondingly covering the dam structure matching data and the dam combination data to obtain the traversal abnormal combination data, wherein the traversal abnormal combination data is data which is not matched with the dam combination data in the dam structure matching data;
s530: and acquiring the coverage traversal result according to the traversal abnormal combination data.
Specifically, a data terminal of a dam structure is connected to acquire dam combination data. The data terminal is a terminal device for gathering dam structure data. The dyke-up data includes dyke-down structure information.
Further, the dam structure matching data and the dam combination data are correspondingly overlaid. And extracting dyke decomposition structure information from dyke combination data and performing traversal matching on dyke structure matching data to obtain a coverage traversal result.
Further, if the dam structure matching data is matched with the dam combination data, acquiring traversal normal combination data and adding the traversal normal combination data to the coverage traversal result. If the dam structure matching data is not matched with the dam combination data, acquiring traversal abnormal combination data and adding the traversal abnormal combination data to the coverage traversal result. Alternatively, the traversal abnormality combination data may include a dyke structure combination abnormality, dyke structure incomplete abnormality, and the like, in which the target dykes are different from the preset dykes in structure.
And performing coverage traversal on the dam structure matching data to acquire coverage traversal data, which is helpful for acquiring abnormal combination data in the traversal data.
The step S600 in the method provided in the embodiment of the present application includes:
s610: performing deviation analysis on the traversal abnormal combination data in the coverage traversal result to obtain abnormal deviation degree;
s620: judging whether the abnormal deviation degree is larger than a preset abnormal deviation degree or not;
s630: if the abnormal deviation degree is larger than the preset abnormal deviation degree, carrying out connectivity analysis on the dyke combination data on the traversal abnormal combination data to obtain a connection coefficient;
s640: determining the structural stability of the target dykes and dams according to the connection coefficients, and obtaining the detection result of the stability of the target dykes and dams;
s650: and marking the quality of the target dykes and dams according to the stability factors in the detection results to obtain quality detection results of the target dykes and dams.
Specifically, deviation analysis is carried out on the traversal abnormal combination data in the coverage traversal result, so that the degree of dispersion of the coverage traversal data is measured, and the abnormal deviation degree of the traversal abnormal combination data is obtained.
Further, a dam quality control standard is acquired based on the big data, and an abnormal deviation degree is preset. And judging whether the abnormal deviation degree is larger than a preset abnormal deviation degree or not. Further, if the abnormal deviation degree is larger than the preset abnormal deviation degree, performing connectivity analysis on the dyke combination data on the traversing abnormal combination data. The connectivity analysis is to analyze structural connectivity and integrity and obtain a connection coefficient.
Further, the structural stability of the target dike is determined according to the connection coefficient. Wherein, the higher the connectivity coefficient, the stronger the dam structure stability. And further obtaining the detection result of the stability of the target dykes and dams. Further, a stability factor in a detection result of the stability of the target dykes is extracted, and the quality of the target dykes is identified according to the stability of the stability factor. And the quality of the target dykes with higher stability is better marked. And further obtaining a quality detection result of the target dam.
And the stability detection is carried out on the structure of the target dam according to the coverage traversal data, so that the quality detection result of the target dam can be obtained according to the detection result.
Example two
Based on the same inventive concept as the dam quality detection method based on the laser point cloud technology in the foregoing embodiments, as shown in fig. 5, the present application further provides a dam quality detection system based on the laser point cloud technology, the system comprising:
the target space three-dimensional coordinate system construction module is used for carrying out data acquisition on the target dykes and dams based on the binocular cameras and constructing a target space three-dimensional coordinate system;
the scanning point position obtaining module is used for scanning the target dykes and dams through a laser point cloud technology to obtain N scanning point positions of the target dykes and dams distributed in the target space three-dimensional coordinate system, wherein N is a positive integer greater than 3;
the target dam three-dimensional structure information acquisition module is used for connecting the N scanning points in the target space three-dimensional coordinate system and determining target dam three-dimensional structure information;
the dam structure matching data acquisition module is used for carrying out information matching on the target dam three-dimensional structure information and a dam structure information base to acquire dam structure matching data;
the coverage traversal data acquisition module is used for carrying out coverage traversal on the dam structure matching data to acquire coverage traversal data, wherein the coverage traversal data comprises traversal abnormal combination data;
the quality detection result obtaining module is used for detecting the stability of the structure of the target dykes and dams according to the coverage traversal data and obtaining the quality detection result of the target dykes and dams according to the detection result.
Further, the system further comprises:
the target original site obtaining module is used for determining a target original site through the binocular camera;
the first coordinate axis construction module is used for constructing a first coordinate axis through the height of the target dykes and dams based on the target original sites;
the second coordinate axis construction module is used for constructing a second coordinate axis based on the target original site and the length of the target dykes;
the third coordinate axis construction module is used for constructing a third coordinate axis through the width of the target dykes and dams based on the target original sites;
the target space three-dimensional coordinate system construction module is used for constructing a target space three-dimensional coordinate system of the target dam based on the first coordinate axis, the second coordinate axis and the third coordinate axis respectively.
Further, the system further comprises:
the scanning reflection point obtaining module is used for carrying out point-by-point scanning on the target dam through a laser radar in the laser point cloud technology to determine a plurality of scanning reflection points, wherein each scanning reflection point in the plurality of scanning reflection points comprises a laser beam;
the three-dimensional coordinate obtaining module is used for configuring the plurality of laser beams in the target space three-dimensional coordinate system in a same ratio mode, and obtaining three-dimensional coordinates of the plurality of scanning reflection points;
and the scanning point position obtaining module is used for determining the N scanning point positions based on the three-dimensional coordinates of the scanning reflection points.
Further, the system further comprises:
the adjacent scanning point position obtaining module is used for extracting a first scanning point position and a second scanning point position of the N scanning point positions, wherein the first scanning point position and the second scanning point position are two adjacent point positions;
the connecting line obtaining module is used for carrying out point location connection on the first scanning point location and the second scanning point location to obtain a plurality of connecting lines;
a three-dimensional data obtaining module for establishing three-dimensional data of the target dike based on the plurality of connecting lines;
the three-dimensional structure information acquisition module is used for constructing the three-dimensional structure information of the target dam according to the three-dimensional data.
Further, the system further comprises:
the decomposition structure acquisition module is used for carrying out structural decomposition on dam structure information in big data to acquire preset dam body structure information, preset dam head structure information and preset dam foundation structure information;
the decomposition structure information acquisition module is used for carrying out structural decomposition on the target dam three-dimensional structure information to acquire dam body structure information, dam head structure information and dam root structure information;
the decomposition structure information matching degree obtaining module is used for sequentially comparing the preset dam body structure information, the preset dam head structure information, the preset dam root structure information with the dam body structure information, the dam head structure information and the dam root structure information to obtain dam body structure information matching degree, dam head structure information matching degree and dam root structure information matching degree;
the dam structure matching data obtaining module is used for determining the dam structure matching data according to the dam body structure information matching degree, the dam head structure information matching degree and the dam root structure information matching degree.
Further, the system further comprises:
a dyke-up data obtaining module for obtaining dyke-up data based on a data terminal of a dyke structure;
the traversal abnormal combination data obtaining module is used for correspondingly covering the dam structure matching data and the dam combination data to obtain traversal abnormal combination data, wherein the traversal abnormal combination data is data which is not matched with the dam combination data in the dam structure matching data;
and the coverage traversal result obtaining module is used for obtaining the coverage traversal result according to the traversal abnormal combination data.
Further, the system further comprises:
the abnormal deviation degree obtaining module is used for carrying out deviation analysis on the traversal abnormal combination data in the coverage traversal result to obtain abnormal deviation degree;
the abnormal deviation judging module is used for judging whether the abnormal deviation is larger than a preset abnormal deviation or not;
the connection coefficient obtaining module is used for carrying out connectivity analysis on the dyke combination data on the traversal abnormal combination data to obtain a connection coefficient if the abnormal deviation degree is larger than the preset abnormal deviation degree;
the detection result obtaining module is used for determining the structural stability of the target dam according to the connection coefficient and obtaining the detection result of the stability of the target dam;
the quality detection result obtaining module is used for marking the quality of the target dykes and dams according to the stability factors in the detection results and obtaining the quality detection results of the target dykes and dams.
A specific example of a laser point cloud technology-based dam quality detection method in the foregoing embodiment is also applicable to a laser point cloud technology-based dam quality detection system in the present embodiment, and by the foregoing detailed description of a laser point cloud technology-based dam quality detection method, those skilled in the art can clearly know a laser point cloud technology-based dam quality detection system in the present embodiment, so that details thereof will not be described herein for brevity of description. The device disclosed in the embodiment corresponds to the method disclosed in the embodiment, so that the description is simpler, and the relevant points refer to the description of the method.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps recited in the present disclosure may be performed in parallel or sequentially or in a different order, provided that the desired results of the technical solutions of the present disclosure are achieved, and are not limited herein.
The above detailed description should not be taken as limiting the scope of the present disclosure. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present disclosure are intended to be included within the scope of the present disclosure.
Claims (6)
1. A dyke quality detection method based on a laser point cloud technology, characterized in that the method is applied to a dyke quality detection system based on a laser point cloud technology, the dyke quality detection system based on a laser point cloud technology being communicatively connected with a binocular camera, the method comprising:
based on the binocular camera, data acquisition is carried out on the target dykes and dams, and a target space three-dimensional coordinate system is constructed;
scanning the target dykes and dams through a laser point cloud technology to obtain N scanning points of the target dykes and dams distributed in the target space three-dimensional coordinate system, wherein N is a positive integer greater than 3;
connecting the N scanning points in the target space three-dimensional coordinate system to determine the three-dimensional structure information of the target dam;
performing information matching on the target dam three-dimensional structure information and a dam structure information base to obtain dam structure matching data;
performing coverage traversal on the dam structure matching data to obtain coverage traversal data, wherein the coverage traversal data comprises traversal abnormal combination data;
performing stability detection on the structure of the target dykes and dams according to the coverage traversal data, and acquiring quality detection results of the target dykes and dams according to detection results;
the coverage traversal data is acquired, and the method further comprises:
acquiring dyke-dam combination data based on a data terminal of the dyke-dam structure;
correspondingly covering the dam structure matching data and the dam combination data to obtain the traversal abnormal combination data, wherein the traversal abnormal combination data is data which is not matched with the dam combination data in the dam structure matching data;
acquiring the coverage traversal data according to the traversal abnormal combination data;
the stability detection is carried out on the structure of the target dykes and dams according to the coverage traversal data, and the quality detection result of the target dykes and dams is obtained according to the detection result, and the method further comprises the following steps:
performing deviation analysis on the traversal abnormal combination data in the coverage traversal data to obtain abnormal deviation degree;
judging whether the abnormal deviation degree is larger than a preset abnormal deviation degree or not;
if the abnormal deviation degree is larger than the preset abnormal deviation degree, carrying out connectivity analysis on the dyke combination data on the traversal abnormal combination data to obtain a connection coefficient;
determining the structural stability of the target dykes and dams according to the connection coefficients, and obtaining the detection result of the stability of the target dykes and dams;
and marking the quality of the target dykes and dams according to the stability factors in the detection results to obtain quality detection results of the target dykes and dams.
2. The method of claim 1, wherein the constructing a target space three-dimensional coordinate system, the method further comprising:
determining a target original site through the binocular camera;
constructing a first coordinate axis through the height of the target dykes based on the target original sites;
constructing a second coordinate axis through the length of the target dykes based on the target original sites;
constructing a third coordinate axis through the width of the target dykes based on the target original sites;
and constructing a target space three-dimensional coordinate system of the target dam based on the first coordinate axis, the second coordinate axis and the third coordinate axis respectively.
3. The method of claim 1, wherein N scan points of the target dam distribution in a target space three-dimensional coordinate system are acquired, the method further comprising:
the target dam is scanned point by point through a laser radar in the laser point cloud technology, and a plurality of scanning reflection points are determined, wherein each scanning reflection point in the plurality of scanning reflection points comprises a laser beam;
the laser beams are arranged in the target space three-dimensional coordinate system in a same ratio mode, and three-dimensional coordinates of the scanning reflection points are obtained;
the N scan points are determined based on the three-dimensional coordinates of the plurality of scan reflection points.
4. The method of claim 1, wherein the determining the three-dimensional structure information of the target dike, the method further comprises:
extracting a first scanning point position and a second scanning point position of the N scanning point positions, wherein the first scanning point position and the second scanning point position are two adjacent point positions;
performing point location connection on the first scanning point location and the second scanning point location to obtain a plurality of connecting lines;
establishing three-dimensional data of the target dike based on the plurality of connecting lines;
and constructing the three-dimensional structure information of the target dam according to the three-dimensional data.
5. The method of claim 1, wherein the obtaining dyke structure matching data, the method further comprising:
performing structural decomposition on dam structure information in big data to obtain preset dam body structure information, preset dam head structure information and preset dam root structure information;
performing structural decomposition on the target dam three-dimensional structure information to obtain dam body structure information, dam head structure information and dam foundation structure information;
sequentially comparing the preset dam body structure information, the preset dam head structure information, the preset dam root structure information with the dam body structure information, the dam head structure information and the dam root structure information to obtain a dam body structure information matching degree, a dam head structure information matching degree and a dam root structure information matching degree;
and determining the dam structure matching data according to the dam body structure information matching degree, the dam head structure information matching degree and the dam root structure information matching degree.
6. A laser point cloud technology-based dyke quality detection system for implementing a laser point cloud technology-based dyke quality detection method as set forth in any one of claims 1-5, the system comprising:
the target space three-dimensional coordinate system construction module is used for carrying out data acquisition on the target dykes and dams based on the binocular cameras and constructing a target space three-dimensional coordinate system;
the scanning point position obtaining module is used for scanning the target dykes and dams through a laser point cloud technology to obtain N scanning point positions of the target dykes and dams distributed in the target space three-dimensional coordinate system, wherein N is a positive integer greater than 3;
the target dam three-dimensional structure information acquisition module is used for connecting the N scanning points in the target space three-dimensional coordinate system and determining target dam three-dimensional structure information;
the dam structure matching data acquisition module is used for carrying out information matching on the target dam three-dimensional structure information and a dam structure information base to acquire dam structure matching data;
the coverage traversal data acquisition module is used for carrying out coverage traversal on the dam structure matching data to acquire coverage traversal data, wherein the coverage traversal data comprises traversal abnormal combination data;
the quality detection result obtaining module is used for detecting the stability of the structure of the target dykes and dams according to the coverage traversal data and obtaining the quality detection result of the target dykes and dams according to the detection result.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102410834A (en) * | 2011-07-29 | 2012-04-11 | 北京航空航天大学 | Dynamic monitoring system device for tailing dam body by three-dimensional laser scanning |
| CN108508033A (en) * | 2018-04-03 | 2018-09-07 | 北京中水科海利工程技术有限公司 | The detecting system and method for a kind of dam face slab open defect and internal soundness |
| CN111373437A (en) * | 2017-11-17 | 2020-07-03 | 柯达阿拉里斯股份有限公司 | Automated online object inspection |
| CN112907511A (en) * | 2021-01-15 | 2021-06-04 | 广州市新誉工程咨询有限公司 | Comprehensive pipe rack information management method and system under BIM technology |
| CN114841944A (en) * | 2022-04-25 | 2022-08-02 | 中钢集团马鞍山矿山研究总院股份有限公司 | Tailing dam surface deformation inspection method based on rail-mounted robot |
| CN115546628A (en) * | 2022-08-29 | 2022-12-30 | 邯郸市亿润工程咨询有限公司 | Hydraulic engineering dam crack monitoring method, device, equipment and medium |
| CN115908424A (en) * | 2023-02-14 | 2023-04-04 | 广东建准检测技术有限公司 | Building health detection method, system and medium based on three-dimensional laser scanning |
| CN116150862A (en) * | 2023-04-23 | 2023-05-23 | 广东广宇科技发展有限公司 | Automatic modeling method for dykes and dams, electronic equipment and computer readable storage medium |
| CN116299522A (en) * | 2022-09-08 | 2023-06-23 | 山东大学 | Dyke apparent disease detection device based on laser radar and camera and working method |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11042146B2 (en) * | 2017-11-17 | 2021-06-22 | Kodak Alaris Inc. | Automated 360-degree dense point object inspection |
-
2023
- 2023-07-12 CN CN202310853488.1A patent/CN116879920B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102410834A (en) * | 2011-07-29 | 2012-04-11 | 北京航空航天大学 | Dynamic monitoring system device for tailing dam body by three-dimensional laser scanning |
| CN111373437A (en) * | 2017-11-17 | 2020-07-03 | 柯达阿拉里斯股份有限公司 | Automated online object inspection |
| CN108508033A (en) * | 2018-04-03 | 2018-09-07 | 北京中水科海利工程技术有限公司 | The detecting system and method for a kind of dam face slab open defect and internal soundness |
| CN112907511A (en) * | 2021-01-15 | 2021-06-04 | 广州市新誉工程咨询有限公司 | Comprehensive pipe rack information management method and system under BIM technology |
| CN114841944A (en) * | 2022-04-25 | 2022-08-02 | 中钢集团马鞍山矿山研究总院股份有限公司 | Tailing dam surface deformation inspection method based on rail-mounted robot |
| CN115546628A (en) * | 2022-08-29 | 2022-12-30 | 邯郸市亿润工程咨询有限公司 | Hydraulic engineering dam crack monitoring method, device, equipment and medium |
| CN116299522A (en) * | 2022-09-08 | 2023-06-23 | 山东大学 | Dyke apparent disease detection device based on laser radar and camera and working method |
| CN115908424A (en) * | 2023-02-14 | 2023-04-04 | 广东建准检测技术有限公司 | Building health detection method, system and medium based on three-dimensional laser scanning |
| CN116150862A (en) * | 2023-04-23 | 2023-05-23 | 广东广宇科技发展有限公司 | Automatic modeling method for dykes and dams, electronic equipment and computer readable storage medium |
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